<h1 id="south-carolina-congressional-districts">2020 South Carolina
Congressional Districts</h1>
<h2 id="redistricting-requirements">Redistricting requirements</h2>
<p>South Carolina has no state constitution or statute for
redistricting. However, the state legislature committees do provide
<em>guidelines</em> for redistricting. (<a
href="https://redistricting.schouse.gov/docs/2021%20Redistricting%20Guidelines.pdf">House
link</a>, <a
href="https://redistricting.scsenate.gov/docs/Senate%20Redistricting%20Guidelines%20Adopted%209-17-21.DOCX">Senate
link</a>), According to these guidelines, districts should:</p>
<ol type="1">
<li>be contiguous (including contiguity by water)</li>
<li>have equal populations as is practicable</li>
<li>comply with VRA Section 2</li>
<li>be geographically compact</li>
<li>preserve boundaries of counties, municipalities, voting tabulation
districts, cores of previous districts, and other communities of
interests as much as possible</li>
<li>preserve separation of incumbents as much as possible</li>
</ol>
<p>The House guidelines state that if the criteria come into conflict,
federal law (including the VRA) and population parity should be
prioritized over others.</p>
<h3 id="algorithmic-constraints">Algorithmic Constraints</h3>
<p>We do not adhere to all criteria in the guidelines. We include the
following constraints:</p>
<ol type="1">
<li>We enforce a maximum population deviation of 0.5%.</li>
<li>We impose a hinge constraint on the Black Voting Age Population so
that it encourages district BVAP of above 40%. Districts with BVAP of
30% or less are not penalized as much. Together, these aim to ensure
that Black voters can elect their candidate of choice in districts with
high BVAP.</li>
<li>We impose a municipality-split constraint to lower the number of
municipality splits.</li>
</ol>
<h2 id="data-sources">Data Sources</h2>
<p>Data for South Carolina comes from the ALARM Project’s <a
href="https://alarm-redist.github.io/posts/2021-08-10-census-2020/">2020
Redistricting Data Files</a>. The state’s new district lines come from
<a
href="https://redistricting.lls.edu/state/south-carolina/?cycle=2020&amp;level=Congress">All
About Redistricting</a>.</p>
<h2 id="pre-processing-notes">Pre-processing Notes</h2>
<p>We take municipalities and concatenate them with counties in order to
apply a constraint to avoid too many municipality splits.</p>
<h2 id="simulation-notes">Simulation Notes</h2>
<p>We sample 6,000 districting plans across two independent runs of the
SMC algorithm. We set the population tempering at 0.05 to avoid
bottlenecks. We then remove all plans that do not contain any district
that has both a BVAP of over 30% and an average voteshare that is more
Democratic than Republican. This remove occurs after verifying that such
plans comprise less than 1% of the 6,000 plans. We then thin the sample
down to exactly 5,000 plans.</p>
<h2 id="contents">Contents</h2>
<ul>
<li><code>SC_cd_2020_stats.csv</code> contains summary statistics on the
sampled redistricting plans</li>
<li><code>SC_cd_2020_plans.rds</code> is a compressed
<code>redist_plans</code> object, which contains the matrix of
precinct/block assignments and may be used for further analysis.</li>
<li><code>SC_cd_2020_map.rds</code> is a compressed
<code>redist_map</code> object, which contains the precinct/block
shapefile and demographic data.</li>
</ul>
<p>Both the <code>redist_plans</code> and <code>redist_map</code> object
are intended to be used with the <a
href="https://alarm-redist.github.io/redist/">redist package</a>.</p>
<h3 id="codebook-for-summary-statistics">Codebook for summary
statistics</h3>
<ul>
<li><code>draw</code>: unique identifier for each sample. Non-numeric
draw names are real-world plans, e.g., <code>cd_2010</code> for an
enacted 2010 plan.</li>
<li><code>district</code>: a district identifier. District numbers
roughly match those in the enacted plan, but the correspondence is not
perfect.</li>
<li><code>chain</code>: a number identifying the run of the
redistricting algorithm used to produce this draw. Used for diagnostic
purposes.</li>
<li><code>pop_overlap</code>: a number indicating the fraction of people
in this plan who reside in the same-numbered district in the enacted
plan.</li>
<li><code>total_pop</code>: the total population of each district.</li>
<li><code>total_vap</code>: the total voting-aged population of each
district.</li>
<li><code>pop_*</code>, <code>vap_*</code>: total (voting-aged)
population within racial and ethnic groups for each district. Variable
codes documented <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>plan_dev</code>: the maximum population deviation among
districts in the plan. Computed as
<code>max(abs(distr_pop - target_pop)/target_pop)</code>.</li>
<li><code>comp_edge</code>: compactness, as measured by the fraction of
internal edges kept. Higher values indicate more compactness.</li>
<li><code>comp_polsby</code>: compactness, as measured by the
Polsby-Popper score. Higher values indicate more compactness.</li>
<li><code>county_splits</code>: the number of counties which belong to
more than one district.</li>
<li><code>muni_splits</code>: the number of Census Designated Places
which belong to more than one district.</li>
<li><code>*_##_dem_*</code>, <code>*_##_rep_*</code>: vote counts for
statewide Democratic and Republican candidates in a certain election.
More information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>adv_##</code>, <code>arv_##</code>: average vote counts for
statewide Democratic and Republican candidates in a certain year. More
information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>ndv</code>, <code>nrv</code>: averages of the
<code>adv_##</code> and <code>arv_##</code> variables across all
available elections.</li>
<li><code>ndshare</code>: normal Democratic share, computed as
<code>ndv / (ndv + nrv)</code></li>
<li><code>e_dvs</code>: average Democratic vote share, computed as the
average of the Democratic vote share when first scored under each
statewide election.</li>
<li><code>pr_dem</code>: probability seat is represented by a Democrat;
calculated as the fraction of statewide elections under which the
district had a majority Democratic share.</li>
<li><code>e_dem</code>: expected number of Democratic seats for the
plan; equivalent to summing the <code>pr_dem</code> values across
districts</li>
<li><code>pbias</code>: partisan bias at 50% vote share, averaged across
all available elections. Positive values indicate Republican bias.</li>
<li><code>egap</code>: the efficiency gap, averaged across all available
elections. Positive values indicate Republican bias.</li>
</ul>
